.add_modelinfo

Model-based trees for subgroup analyses in clinical trials and
model-based forests for the estimation and prediction of personalised
treatment effects (personalised models). Currently partitioning of linear
models, lm(), generalised linear models, glm(), and Weibull models,
survreg(), is supported. Advanced plotting functionality is supported for
the trees and a test for parameter heterogeneity is provided for the
personalised models. For details on model-based trees for subgroup analyses
see Seibold, Zeileis and Hothorn (2016) <doi:10.1515/ijb-2015-0032>; for
details on model-based forests for estimation of individual treatment effects
see Seibold, Zeileis and Hothorn (2017) <doi:10.1177/0962280217693034>.

Heidi Seibold

model4you

Stratified and Personalised Models Based on Model-Based Trees
and Forests

Achim Zeileis

Torsten Hothorn

.add_modelinfo function

<dl><dt>x</dt>
<dd>constparty object.</dd>
<dt>nodeids</dt>
<dd>node ids, usually the terminal ids.</dd>
<dt>data</dt>
<dd>data.</dd>
<dt>model</dt>
<dd>model.</dd>
<dt>coeffun</dt>
<dd>function that takes the model object and returns the coefficients.
Useful when coef() does not return all coefficients (e.g. survreg).</dd></dl>

Arguments

Add model information to a personalised-model-ctree — .add_modelinfo

<dl>

<dt>x</dt>
<dd>constparty object.</dd>


<dt>nodeids</dt>
<dd>node ids, usually the terminal ids.</dd>


<dt>data</dt>
<dd>data.</dd>


<dt>model</dt>
<dd>model.</dd>


<dt>coeffun</dt>
<dd>function that takes the model object and returns the coefficients.
Useful when coef() does not return all coefficients (e.g. survreg).</dd>

</dl>

.add_modelinfo: Add model information to a personalised-model-ctree

Description

Usage

Value

Arguments